Cancer Genomics

Gene Expression Profiling

Cancer causes the deregulation of normal cellular processes such as growth, proliferation, migration, differentiation (changes in cell structure and function), and apoptosis (programmed cell death). Gene expression changes that cause or result from this deregulation can be detected by changes in the amount of mRNA being transcribed from the DNA sequences of genes involved in particular processes.

Introduction

LICR scientists are using cutting-edge technologies to compare gene expression in cancer and normal cells, and identify changes that occur during cancer progression. Identifying expression changes may help further our understanding of how and why cancer occurs, allow the development of better screening techniques to diagnose cancer before it becomes life-threatening, identify targets for therapy, and may also be used to give prognostic information, and determine optimal treatment(s).

Massively-Parallel Signature Sequencing

Massively-parallel signature sequencing (MPSS) is a technology, theoretically able to identify and quantify almost all genes expressed in a given cell type. In MPSS, the mRNA sequence of each gene in a particular sample is proportionally amplified (replicated) and then sequenced. The number of RNA sequences that match a particular gene’s DNA sequence is used to represent that gene’s level of expression. Because MPSS detects very rare mRNA species, it provides a more comprehensive analysis than microarray technology (below), but has less potential as a diagnostic or prognostic technology due to its cost and complexity.

LICR investigators from the Lausanne and UCL Branches and the New York Office led an academic and commercial collaboration to analyze 32 normal human tissues with MPSS and documented the expression of almost 20,000 genes with high sensitivity and specificity(1). The results confirmed the hypothesis that gene expression differences between tissue types is determined largely by a limited number of tissue-specific genes. All MPSS data from LICR studies(1,2) have been made freely available on the web at http://mpss.licr.org, and should prove useful for the study of gene expression changes induced by cancer and other diseases. MPSS data are also being mined by LICR investigators to identify gene targets (see ‘Gene Discovery & Characterization’) for potential cancer immunotherapies.

Microarray Technology

Microarray

Microarray analysis allows comparative gene expression between two samples (more...)

High through-put gene expression, or ‘transcription’, profiling can also be performed using microarrays, also known as ‘gene chips’. The RNA from a cancer sample and RNA from a normal sample, for example, are each labeled with a different color fluorescent dye and the samples are hybridized competitively to gene sequences ‘spotted’ onto a glass slide. The hybridization, as measured by the fluorescent dye signal from each gene’s ‘spot’, gives a comparative measure of gene expression.

In 1999, the LICR, together with Cancer Research UK (London, UK), and the Wellcome Trust Sanger Institute (Cambridge, UK) formed a Microarray Consortium to produce high quality microarrays for LICR and Cancer Research UK scientists and their collaborators. The LICR São Paulo Branch set up a second microarray facility to take advantage of the RNA transcripts produced through the Human Cancer Genome Project.

Gastric and Esophageal Cancer

In two separate studies, a team from the LICR São Paulo Branch investigated early transcription changes in gastric cancer and non-malignant gastric mucosa(3) and characterized malignant and non-malignant changes in the stomach and esophagus(4) using microarrays produced by the LICR São Paulo Microarray Laboratory. Both studies were featured on the front cover of the American Association for Cancer Research’s journal, Cancer Research. Gastric and esophageal cancers have high mortality rates, primarily because the symptoms appear late in disease progression and treatment options are then limited. Identifying early transcription changes is the first step in developing screening tests for earlier diagnosis, and thus improved mortality rates.

Breast Cancer

A longstanding collaboration between the LICR’s UCL and São Paulo Branches has used microarray technologies to investigate gene expression changes in breast cancers. The team studied normal breast cell types - luminal epithelial and myopepithelial cells - and identified potential prognostic markers in breast tumor samples based on cell type-specific gene expression(5). The team also characterized genes up-regulated by ErbB-2/HER-2 receptor tyrosine kinase overexpression(6), which is commonly found in breast cancer. Determining which pathways downstream of the ErbB-2 receptor are activated during carcinogenesis may help to identify new targets for prognosis and therapy.

Reprogramming of Transcription in Tumor Invasion

Differentiation from an epithelial cell to a more motile mesenchymal cell - epithelial-mesenchymal transition (EMT) - is a first step in tumor invasion and metastasis. LICR investigators from the Uppsala Branch analyzed the transcription profiles in various mouse and human epithelial cells following stimulation with different TGF-β family members(7). This study is the first step in the decryption of genetic networks downstream of TGF-β, which link cell proliferation and EMT. This knowledge is critical to identifying candidate targets for therapies that might prevent EMT.

References

  1. Jongeneel C.V., Delorenzi M., Iseli C., Zhou D., Haudenschild C.D., Khrebtukova I., Kuznetsov D., Stevenson B.J., Strausberg R.L., Simpson A.J., and Vasicek T.J. An atlas of human gene expression from massively parallel signature sequencing (MPSS). Genome Res. (2005) 15(7):1007-1014
  2. Jongeneel C.V., Iseli C., Stevenson B.J., Riggins G.J., Lal A., Mackay A., Harris R.A., O'Hare M.J., Neville A.M., Simpson A.J., and Strausberg R.L. Comprehensive sampling of gene expression in human cell lines with massively parallel signature sequencing. Proc.Natl.Acad.Sci.U.S.A (2003) 100(8):4702-4705.
  3. Meireles S.I., Cristo E.B., Carvalho A.F., Hirata R., Jr., Pelosof A., Gomes L.I., Martins W.K., Begnami M.D., Zitron C., Montagnini A.L., Soares F.A., Neves E.J., and Reis L.F. Molecular classifiers for gastric cancer and nonmalignant diseases of the gastric mucosa. Cancer Res. (2004) 64(4):1255-1265.
  4. Gomes L.I., Esteves G.H., Carvalho A.F., Cristo E.B., Hirata R., Jr., Martins W.K., Marques S.M., Camargo L.P., Brentani H., Pelosof A., Zitron C., Sallum R.A., Montagnini A., Soares F.A., Neves E.J., and Reis L.F. Expression profile of malignant and nonmalignant lesions of esophagus and stomach: differential activity of functional modules related to inflammation and lipid metabolism. Cancer Res. (2005) 65(16):7127-7136.
  5. Jones C., Mackay A., Grigoriadis A., Cossu A., Reis-Filho J.S., Fulford L., Dexter T., Davies S., Bulmer K., Ford E., Parry S., Budroni M., Palmieri G., Neville A.M., O'Hare M.J., and Lakhani S.R. Expression profiling of purified normal human luminal and myoepithelial breast cells: identification of novel prognostic markers for breast cancer. Cancer Res (2004) 64(9):3037-3045.
  6. Mackay A., Jones C., Dexter T., Silva R.L., Bulmer K., Jones A., Simpson P., Harris R.A., Jat P.S., Neville A.M., Reis L.F., Lakhani S.R., and O'Hare M.J. cDNA microarray analysis of genes associated with ERBB2 (HER2/neu) overexpression in human mammary luminal epithelial cells. Oncogene (2003) 22(17):2680-2688.
  7. Valcourt U., Kowanetz M., Niimi H., Heldin C.H., and Moustakas A. TGF-beta and the Smad signaling pathway support transcriptomic reprogramming during epithelial-mesenchymal cell transition. Mol.Biol.Cell (2005) 16(4):1987-2002.

Centers Involved in this Research